Σύγκριση μεθόδων

	Πειραματικός Σχεδιασμός Πλήρους Παραγοντικού Τύπου	Δοκιμή H Kruskal-Wallis	Μονόδρομη Ανάλυση Διακύμανσης
Πεδίο	Πειραματικός Σχεδιασμός	Στατιστική	Στατιστική
Οικογένεια	Hypothesis test	Hypothesis test	Hypothesis test
Έτος προέλευσης	1926	1952	1925
Δημιουργός	R. A. Fisher	William Kruskal & W. Allen Wallis	Ronald A. Fisher
Τύπος	Parametric factorial experiment	Nonparametric group comparison	Parametric mean comparison
Θεμελιώδης πηγή	Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley. ISBN: 978-0471718130	Kruskal, W. H. & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47(260), 583–621.	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.
Εναλλακτικές ονομασίες	factorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k)	Kruskal-Wallis H test, one-way ANOVA on ranks, Kruskal-Wallis one-way analysis of variance, Kruskal-Wallis Testi	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
Συναφείς	5	5	4
Σύνοψη	A full factorial design is a parametric experimental method in which every combination of factor levels is tested simultaneously, enabling the estimation of all main effects and all interaction effects in a single study. Rooted in R. A. Fisher's foundational work on designed experiments (1926) and systematically developed by Box, Hunter, and Hunter (2005) and Montgomery (2017), the 2^k form tests k two-level factors across 2^k experimental runs and is the benchmark against which all other factorial designs are measured.	The Kruskal-Wallis H test is a nonparametric hypothesis test that compares three or more independent groups to decide whether their distributions (typically their medians) differ. Introduced by William Kruskal and W. Allen Wallis in 1952, it works on ranks rather than raw values and is the distribution-free counterpart to one-way ANOVA.	One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925.